/Mikael
You are welcome to attend Johan Hagelbäck's licentiate seminar at the School of Information and Communication Technology, Blekinge Institute of Technology.
Time : 10-12, April 17
Place : Smaragden, Soft Center Ronneby
Thesis title : "A Multi-Agent Potential Field based approach for Real-Time Strategy Game bots"
Research education subject : Computer Science
Examiner and advisor: Professor Paul Davidsson, BTH
Main Advisor: Associate Professor Stefan Johansson, BTH
Assistant Advisor: Professor Craig Lindley, BTH
Opponent: Julian Togelius, Istituto Dalle Molle di Studi sull'Intelligenza Artificiale, Lugano, Schweiz
The thesis is available at: http://www.bth.se/tek/jhg.nsf/sidor/lic
After the seminar there will be some refreshments. Please contact Monica Nilsson (monica.h.nilsson@bth.se or 0457-385842) if you intend to participate.
Please forward this information to anyone who might be interested in this matter.
Abstract:
Computer games in general and Real-Time Strategy (RTS) games in particular provide a rich challenge for both human- and computer controlled players, often denoted as bots. The player or bot controls a large number of units that have to navigate in partially unknown dynamic worlds to pursue a goal. Navigation in such worlds can be complex and require much computational resources.
Typically it is solved by using some sort of path planning algorithm, and a lot of research has been conducted to improve the performance of such algorithms in dynamic worlds. The main goal of this thesis is to investigate an alternative approach for RTS bots based on Artificial Potential Fields, an area originating from robotics. In robotics the technique has successfully been used for navigation in dynamic environments, and we show that it is possible to use Artificial Potential Fields for navigation in an RTS game setting without any need of path planning.
In the first three papers we define and demonstrate a methodology for creating multi-agent potential field based bots for an RTS game scenario where two tank armies battle each other. The fourth paper addresses incomplete information about the game world, referred to as the fog of war, and show how Potential Field based bots can handle such environments. The final paper shows how a Potential Field based bot can be evolved to handle a more complex full RTS scenario. It addresses resource gathering, construction of bases, technological development and construction of an army consisting of different types of units.
We show that Artificial Potential Fields is a viable option for several RTS game scenarios and that the performance, both in terms of being able to win a game and computational resources used, can match and even surpass those of traditional approaches based on path planning.
Time : 10-12, April 17
Place : Smaragden, Soft Center Ronneby
Thesis title : "A Multi-Agent Potential Field based approach for Real-Time Strategy Game bots"
Research education subject : Computer Science
Examiner and advisor: Professor Paul Davidsson, BTH
Main Advisor: Associate Professor Stefan Johansson, BTH
Assistant Advisor: Professor Craig Lindley, BTH
Opponent: Julian Togelius, Istituto Dalle Molle di Studi sull'Intelligenza Artificiale, Lugano, Schweiz
The thesis is available at: http://www.bth.se/tek/jhg.nsf/sidor/lic
After the seminar there will be some refreshments. Please contact Monica Nilsson (monica.h.nilsson@bth.se or 0457-385842) if you intend to participate.
Please forward this information to anyone who might be interested in this matter.
Abstract:
Computer games in general and Real-Time Strategy (RTS) games in particular provide a rich challenge for both human- and computer controlled players, often denoted as bots. The player or bot controls a large number of units that have to navigate in partially unknown dynamic worlds to pursue a goal. Navigation in such worlds can be complex and require much computational resources.
Typically it is solved by using some sort of path planning algorithm, and a lot of research has been conducted to improve the performance of such algorithms in dynamic worlds. The main goal of this thesis is to investigate an alternative approach for RTS bots based on Artificial Potential Fields, an area originating from robotics. In robotics the technique has successfully been used for navigation in dynamic environments, and we show that it is possible to use Artificial Potential Fields for navigation in an RTS game setting without any need of path planning.
In the first three papers we define and demonstrate a methodology for creating multi-agent potential field based bots for an RTS game scenario where two tank armies battle each other. The fourth paper addresses incomplete information about the game world, referred to as the fog of war, and show how Potential Field based bots can handle such environments. The final paper shows how a Potential Field based bot can be evolved to handle a more complex full RTS scenario. It addresses resource gathering, construction of bases, technological development and construction of an army consisting of different types of units.
We show that Artificial Potential Fields is a viable option for several RTS game scenarios and that the performance, both in terms of being able to win a game and computational resources used, can match and even surpass those of traditional approaches based on path planning.
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